Computer implemented method for tracking and checking measures and computer programs thereof

Abstract

A computer implemented method for tracking and checking measures and computer programs thereof. A master node receiving from a plurality of slaves nodes messages related with measures generated by the slaves nodes, the method including: capturing, a traffic driver unit, the messages sent by the slaves nodes and further sending them to a monitor unit; analyzing, the monitor unit, the received messages so as to detect, by a behavioral learning technique, anomalies in the messages; when an anomaly is detected, sending, the monitor unit, the detected anomaly to a regenerator unit for regenerating at least the detected anomaly by a prediction technique; and injecting, said traffic drive unit, measures regenerated by the regenerator unit to the transport network.

1 . A computer implemented method for tracking and checking measures, wherein a master node comprises receiving from a plurality of slaves nodes messages related with measures generated by the slaves nodes, the method being characterized in that comprises the following steps:
 capturing, a traffic driver unit, said messages sent by the slaves nodes and further sending them to a monitor unit;   analyzing, said monitor unit, the received messages so as to detect, by means of a behavioral learning technique, anomalies in said messages;   when an anomaly is detected, sending, said monitor unit, the detected anomaly to a regenerator unit for regenerating at least the detected anomaly by means of a prediction technique; and   injecting, said traffic drive unit, measures regenerated by said regenerator unit to the transport network.   
     
     
         2 . A method according to  claim 1 , further comprising when an anomaly is not detected, returning, said monitor unit, the received messages to said traffic driver unit, the traffic driver unit progressing the messages to said transport network. 
     
     
         3 . A method according to  claim 1 , wherein said captured messages are decoded, previous to said sending, in an abstract representation to extract the related measures. 
     
     
         4 . A computer implemented method according to  claim 3 , wherein said analyzing further comprises modeling said decoded messages by executing at least one of:
 identifying the received messages, computing the frequency in which the messages were sent, computing the number of different production measures contained in the messages, computing the maximum and minimum values the measures can take and/or computing the repetition rate of the measures.   
     
     
         5 . A computer implemented method according to  claim 4 , comprising detecting said anomaly by comparing the received messages with said modeled messages. 
     
     
         6 . A computer implemented method according to  claim 4 , comprising storing said modeled messages in a models repository unit. 
     
     
         7 . A computer implemented method according to  claim 1 , wherein said detected anomaly sent comprises the following information: original message information, type of the detected anomaly, a specific message identifier, and an abnormal measure index. 
     
     
         8 . A computer implemented method according to  claim 1 , comprising performing the regeneration or prediction of said detected anomaly based on previous recent values of the measures, being said previous recent values of the messages previously gathered by said monitor module and stored in said models repository unit. 
     
     
         9 . A computer implemented method according to  claim 8 , wherein said prediction technique comprises at least one of an extrapolation, interpolation, regression, principal component analysis or a temporal memories technique. 
     
     
         10 . A computer implemented method according to  claim 1 , wherein said detected anomaly comprises at least one of a lost message, a received message containing not updated measures and/or a received message containing measures out of an expected range. 
     
     
         11 . A computer implemented method according to  claim 1 , wherein said behavioral learning technique comprises at least a statistic technique or a machine learning technique. 
     
     
         12 . A computer implemented method according to  claim 1 , comprising performing said capturing every certain period of time. 
     
     
         13 . A computer implemented method according to  claim 1 , wherein said messages are SCADA messages. 
     
     
         14 . A computer program comprising computer program code means adapted to perform all the steps of  claim 1  when said program is run on a computer. 
     
     
         15 . A computer program comprising computer program code means adapted to perform  claim 2  when said program is run on a computer.